Triple

T28423148
Position Surface form Disambiguated ID Type / Status
Subject Peg Maltby E719996 entity
Predicate birthName P65 FINISHED
Object Agnes Newberry Orchard
Agnes Newberry Orchard, better known by her professional name Peg Maltby, was an English-born Australian illustrator and children's book author celebrated for her whimsical fairy-tale artwork.
 E1818280 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Agnes Newberry Orchard | Statement: [Peg Maltby, birthName, Agnes Newberry Orchard]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Agnes Newberry Orchard
Triple: [Peg Maltby, birthName, Agnes Newberry Orchard]
Generated description
Agnes Newberry Orchard, better known by her professional name Peg Maltby, was an English-born Australian illustrator and children's book author celebrated for her whimsical fairy-tale artwork.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69eff6f1c5088190bc24bfbf92f9c017 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64dfc22188190a71aa737d6320d61 completed May 2, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1633200c848190a090a4d9ac51a805 completed May 26, 2026, 11:56 p.m.
NEDg Description generation batch_6a1637ddea1481908ca179d2d895c13e completed May 27, 2026, 12:16 a.m.
NED2 Entity disambiguation (via description) batch_6a163b8d5e948190ac304fc31d6624bf completed May 27, 2026, 12:32 a.m.
Created at: April 28, 2026, 1:35 a.m.